License to Skill: Everything You Need to Take Your AI Agent Game to the Next Level

At Dryft , we build systems that replicate human decisions in industrial operations, through a combination of AI agents and mathematical optimization and simulation. Our agents analyze data and enterpise context to provide actionable recommendations, all in real-time conversations with domain experts. All of our agents are built on Pydantic AI (We are big fans of Pydantic ). In this article we will use Pydantic AI as our point of reference for building agents, but the techniques and the concepts mentioned in the article should be applicable to any agentic framework. The agents live under their own domain, as we follow Domain Driven Design (DDD). That means all core agent logic is implemented concretely in its own distinct domain, and not mixed with API routes, database models, or other concerns. This keeps the codebase clean and maintainable. This post will explore some agent structuring patterns, from the simplest pattern to the most complex, along with the reasoning behind when to us